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Cyclone activities as inferred from the Twentieth Century Reanalysis version 3 (20CRv3) for 1836-2015

2020· article· en· W3083458932 on OpenAlexaff
Xiaolan Wang, Yang Feng, Rodney Chan, Gilbert P. Compo, Laura Slivinski, Bin Yu, Michael Wehner, Xiao‐Yi Yang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsNorthern HemisphereCyclone (programming language)ClimatologyMeteorologyEnvironmental sciencePeriod (music)Atmospheric sciencesComputer sciencePhysicsGeology

Abstract

fetched live from OpenAlex

Preliminary results obtained from tracking cyclones in the ensemble-average and individual members of the NOAA-CIRES-DOE Twentieth Century Reanalysis version 3 (20CRv3) ensemble for the period 1836-2015 will be presented. Comparison with tracking in the 20CRv2c ensemble-average series will also be shown. The results indicate that the 20CRv3 is an improvement in representing cyclone climate and variability compared to previous versions (20CRv2c or 20CRv2). However, as in previous versions, the 20CRv3 ensemble-average fields are too smooth to use for tracking cyclones and studying cyclone climate, especially for the period before 1960 for the NH and for the entire reanalysis period for the SH, and that there are still temporal inhomogeneity issues in the 20CRv3, especially in the SH and in the early period for the NH, due to the increases over time of observations available for assimilation. The improvements arise from the use of a higher model resolution and the assimilation of more observations. They include that the 20CRv3 ensemble shows cyclones of higher intensities and a higher number of deep cyclones (center pressure ≤ 960 hPa) in the Northern Hemisphere than the 20CRv2c counterpart. Historical trends of cyclone activity and their uncertainties will be discussed based on the results of tracking the individual members of the 20CRv3 ensemble, with the temporal inhomogeneity issues being taken into account.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.023
GPT teacher head0.248
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2020
Admission routes1
Has abstractyes

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